The article "Bone Density and Insertion Torque as Predictors of Anterior Cruciate Ligament Graft Fixation Strength"t gave the accompanying data on maximum insertion torque (N• m) and yield load (N), the latter being onemeasure of graft strength, for 15 different specimens.Torque1.82.21.91.32.12.21.62.11.21.82.62.52.51.71.6Load491477598361605671 466431384422554577642348446(a) Is it plausible that yield load is normally distributed?Yes, there are more than thirty data values.No, a normal probability plot of yield load is not quite linear.Yes, a normal probability plot of yield load is quite quadratic.No, there is not more than thirty data values.Yes, a normal probability plot of yield load is quite linear.(b) Estimate true average yield load by calculating a confidence interval with a confidence level of 95%. (Round your answer to two decimal places.)Interpret the interval.We are 95% confident that the true population average yield load lies below this interval.We are 95% confident that this interval does not contain the true average yield load.We are 95% confident that the true population average yield load lies above this interval.We are 95% confident that this interval contains the true average yield load.(c) Here is output from Minitab for the regression of yield load on torque.PredictorCoefSE CoefTPConstant152.4491.171.670.118Torque178.2345.973.880.002S = 73.2141R-Sq53.6%R-Sq (adj)50.0%SourceDFSMSFPRegression1805548055415.030.002Residual Error13696845360Total14150238Does the simple linear regression model specify a useful relationship between the variables?Yes, the t-statistic and P-value are significant at any reasonable level, so we can conclude that a useful linear relationship exists.No, the t-statistic and P-value are not significant at any reasonable level, so we can conclude that a useful linear relationship exists.Yes, the t-statistic and P-value are significant at any reasonable level, so we cannot conclude that a useful linear relationship exists.No, the t-statistic and P-value are not significant at any reasonable level, so we cannot conclude that a useful linear relationship exists.

Given data: Torque (y) 1.8 2.2 1.9 1.3 2.1 2.2 1.6 2.1 1.2 1.8 2.6 2.5 2.5 1.7 1.6 Load (x) 491…

The article "Bone Density and Insertion Torque as Predictors of Anterior Cruciate Ligament Graft Fixation Strength"t gave the accompanying data on maximum insertion torque (N · m) and yield load (N), the latter being one measure of graft strength, for 15 different specimens. Torque 1.8 2.2 1.9 1.3 2.1 2.2 1.6 2.1 1.2 1.8 2.6 2.5 2.5 1.7 1.6 Load 491 477 598 361 605 671 466 431 384 422 554 577 642 348 446 (a) Is it plausible that yield load is normally distributed? O Yes, there are more than thirty data values. O No, a normal probability plot of yield load is not quite linear. O Yes, a normal probability plot of yield load is quite quadratic. No, there is not more than thirty data values. Yes, a normal probability plot of yield load is quite linear. (b) Estimate true average yield load by calculating a confidence interval with a confidence level of 95%. (Round your answer to two decimal places.) Interpret the Interval. O we are 95% confident that the true population average yield load lies below this interval. We are 95% confident that this interval does not contain the true average yield load. O we are 95% confident that the true population average yield load lies above this interval. We are 95% confident that this interval contains the true average yield load. (c) Here is output from Minitab for the regression of yield load on torque. Predictor Coef SE Coef T P Constant 152.4 91.17 1.67 0.118 Torque S = 73.2141 178.23 45.97 3.88 0.002 R-Sq = 53.6% R-Sq (adj) = 50.0% Source DF MS F P Regression 80554 80554 15.03 0.002 Residual Error 13 69684 5360 Total 14 150238 Does the simple linear regression model specify a useful relationship between the variables? O Yes, the t-statistic and P-value are significant at any reasonable level, so we can conclude that a useful linear relationship exists. O No, the t-statistic and P-value are not significant at any reasonable level, so we can conclude that a useful linear relationship exists. O Yes, the t-statistic and P-value are significant at any reasonable level, so we cannot conclude that a useful linear relationship exists. O No, the t-statistic and P-value are not significant at any reasonable level, so we cannot conclude that a useful linear relationship exists.